Introduction to Diploma Logistics, and couple of labs to setup the tools, and environments we will need for the start of the Journey

Understand the basic and fundamental concepts and technologies used in the field currently, this is a very important and essential course that we will use concepts we will learn there many times during the next courses

In this course, we will go into the backend of how databases work, which is very important for you as data engineer and data professional in general to be able to utilize the database systems and get the best out of it.

We will learn about how database store files, how it retrieves it, how queries is executed, and some of the concepts we will use as well in the coming courses

Covering the fundamentals of Python Programming language and how to do execute data engineering and data transformation jobs using libraries such as Pandas and Numpy

Every data engineer either working on-premise or cloud will have to deal with Linux systems at some point of time, so in this course, we will cover linux fundamentals and how to write shell/bash scripts to automate some tasks.

Introduction to Big Data concepts and current technologies, and go deeply into Apache Hadoop & YARN components and do hands-on labs to cover the main concepts of the solution.

Apache Hive is essential components in big data ecosystem, it provides a SQL like interface on top of your data lake storage which gives you flexibility to develop easy to read and easy to use applications without programming needed.

In this course, we will cover all the basic concepts of Apache Hive, HiveQL syntax, and how to design your data layers in Apache Hive.

Apache Spark is the star of big data processing, its till now, the go to processing engine when developing big data applications.

In this course, we will learn about Apache Spark components, what makes it unique, how to develop using Apache Spark API such as Dataframes, also we will get introduction to Databricks as a platform and why databricks is unique platform in todays market.

Streaming use cases deployment increasing currently in the market, and learning how to develop streaming pipelines is essential tool in data engineer skills stack.

In this Course, we will cover streaming pipelines fundamental concepts, and how to develop structured streaming applications in Apache Spark, we will learn about Watermarks, triggers and more.

Apache Kafka is the star when it comes to streaming, Apache Kafka is a solid event hub and a core part of the streaming pipelines, and Kafka Connect, is add-on on top of Apache Kafka to expand Kafka Connectivity.

In this course, we will cover Apache Kafka components, and how to interact with Kafka through different API such as CLI and Python API, how to develop Python applications to interact with Apache Kafka.

DBT becoming increasingly popular due to the increase of cloud warehouses and modern data lakehouse solutions such as Snowflake. In this course, we will cover how to build dbt projects and how to use the main structures of dbt to develop modern ELT pipelines.

Apache Airflow is orchestrator that became part of the modern data architecture nowadays with the rising of data lakehouse concepts. In this course, we will learn all about designing and executing of Airflow DAGs.

In this course, we will cover the key features of AWS cloud data platform, and AWS Big Data Services in specific, such as EMR, S3, Athena, and more.

In this course, we will cover the key features of Azure cloud data platform, and Azure Big Data Services in specific, such as Azure HDInsights, ADLS, and more.